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Record W2249130963

協商加拿大華裔身份認同:黎熹年《鹹魚妹》中的記憶與他者

2014· dissertation· zh· W2249130963 on OpenAlexaboutno aff
黃孟純, Meng-Chun Huang

Bibliographic record

Venue成功大學外國語文學系學位論文 · 2014
Typedissertation
Languagezh
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsHybridityNarrativeIdentity (music)EssentialismMythologyEmbodied cognitionStyle (visual arts)LiteratureAestheticsSociologyArtGender studiesPhilosophyEpistemology
DOInot available

Abstract

fetched live from OpenAlex

Larissa Lai’s Salt Fish Girl features mixed genres and alternate narrative style, with allusions to the Chinese mythological folktale, Nu Wa’s Creation of Mankind, and the Western fairy tale, The Little Mermaid. The “hybridized” writing style is strategically employed to reflect the hybridity of the Asian Canadian identity. This thesis intends to investigate how the Asian Canadian identity is negotiated in the process of creating a fake memory and in the encounter of the other. The first chapter explores how the narrator I embodies the multifarious voices in the distinct memory narratives in the process of doing the remembering in order to deconstruct fixed and essentialist representations of the Asian Canadian identity. The second chapter further explores otherness, embodied by the smells, and how the smells function to distinguish between one and the other and between the other and other others. The thesis concludes with the reflection on the limits of the thesis and with a response to Julia Kristeva’s claim on love for strangers.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.205
Threshold uncertainty score0.413

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0170.012
Scholarly communication0.0070.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.245
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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